# always clean up R environment
rm(list = ls())
# load all packages here
# Basic Data Analysis & Wrangling
library(tidyverse)
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library(lubridate)
Attaching package: ‘lubridate’
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# Library for splitting the chinese words.
library(jiebaRD)
library(jiebaR)
package ‘jiebaR’ was built under R version 3.5.2
# Library for generating word cloud.
library(wordcloud)
Loading required package: RColorBrewer
# Library for visualizing the 3d plot.
library(plotly)
Attaching package: ‘plotly’
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A couple companies have tried to enter the lucrative market of mainland China, however, many of them faced obstacles. A famous example is from Google, who specifically designed the dragonfly plan for Chinese Market, that failed due to regulation as well as lack of interest from the general public. eBay was one of the earliest counterparts that laid eyes on Asia market, and all of these big companies failed for the same reason: they all had unsuccessful integration of incompatible cultures. We personally call it “attempt of cultural imperialism within the field of internet.” The big companies took over many places with success without changing much of its business model, or approach of the local audience. However, there is a tremendous culture difference between western and eastern society. One example is the young generate in the United States use Facebook, Twitter, Instagram, Snapchat and other social platforms simultaneously. Teens in China all only use one social media app, Wechat, that could also pay for bills, call an uber, book a movie, find the restaurant. Consumer behavior and culture difference is what pulled these big companies back.
Chinese government is known for its regulation and censorship. According to an article published by New York Times, the new president hopes to use the Internet to strengthen Communist Party’s role on the society. Majority of the young generation is indifferent to politics, although many are victims of censorship as well as censorship factory workers.
dt_issues = read.csv("data/issues_data.csv", header=TRUE)
dt_star = read.csv("data/stargazers.csv", header=TRUE)
dt_user = read.csv("data/users_data.csv", header=TRUE)
# Inspect the dataset by taking the first 10 rows of each dataset.
dt_issues %>% head(10)
dt_star %>% head(10)
dt_user %>% head(10)